Embodiments according to the invention are related to a noise filler for providing a noise-filled spectral representation of an audio signal on the basis of an input spectral representation of the audio signal, to a noise filling parameter calculator for providing a noise filling parameter on the basis of a quantized spectral representation of an audio signal, to an encoded audio signal representation representing an audio signal, to a method for providing a noise filled spectral representation of an audio signal, to a method for providing a noise filling parameter on the basis of a quantized spectral representation of an audio signal, and to computer programs for implementing said methods.
In the following, some scenarios will be described in which embodiments according to the invention can be applied with advantage. Many frequency domain audio signal encoders are based on the idea that some frequency regions or spectral regions (e.g. frequency lines or spectral lines provided by a time-domain to frequency-domain conversion), are more important that other spectral regions. Accordingly, spectral regions of high psychoacoustic relevance are typically encoded with higher accuracy than spectral regions of lower psychoacoustic relevance. The psychoacoustic relevance of the different spectral regions may, for example, be calculated using a psychoacoustic model which takes into account the masking of weaker spectral regions by adjacent strong spectral peaks.
If there is a desire to reduce the bitrate of an encoded audio signal down towards a low level, some spectral regions are quantized with a very low accuracy (e.g. only one bit accuracy, or two bit accuracy). Accordingly, many of the spectral regions quantized with low accuracy are quantized to zero. Thus, at low bitrates transform-based audio coders are prone to different artifacts and especially to artifacts originating from the zero-quantized frequency lines. Indeed, coarse quantization of spectral values in low bitrate audio coding might lead to very sparse spectra after inverse quantization, as many spectral lines might have been quantized to zero. These frequency holes in the reconstructed signal produce undesirable sound artifacts. It can make the reproduced sound too sharp or instable (birdies) when the frequency holes in the spectra move from frame to frame.
Noise filling is a means to mask these artefacts by filling, at the decoder side, the zero-quantized coefficients or bands with a random noise. The energy of the inserted noise is a parameter computed and transmitted by the encoder.
Different concepts of noise filling are known. For example, the so-called AMR-WR+ combines noise filling and a Discrete Fourier Transform (DFT), as described for example in reference [1]. In addition, the International Standard ITU-T G.729.1 defines a concept which combines noise filling and modified discrete cosine transform (MDCT). Details are described in reference [2].
Further aspects regarding the noise filling are described in the International patent application PCT/IB2002/001388 by Koninklijke Philips Electronics N.V. (see reference [3]).
Nevertheless, the conventional noise filling concepts result in audible distortions.
In view of this discussion, there is a desire to create a concept of noise filling which provides for an improved hearing impression.